EMBRIO Multiscale Modeling E-Book

Contents:

• Notes on Current Build (0.999…)
  • Known Issues
  • Content Update Schedule
• Introduction
  • Why Learn Modeling?
  • Learning Objectives
  • How to Use This Site
• Module 0: Introduction to Scientific Computing
  • 0.1 Mathematical Operations, Defining Variables, and Plotting
  • 0.2: Loops and Logic
  • 0.3: Making Reusable Code — Defining Functions
  • 0.4: Answers for the exercises
• Module 1: Introduction to Biological Modeling
  • 1.1 The Biological Modeling Workflow
  • 1.2: Worked Example : Cell Sorting
  • 1.3: Exercises
• Module 2: Building Mathematical Models
  • 2.1: Modeling with Differential Equations
  • 2.2: Partial Differential Equations
  • 2.3: The Finite Difference Method
• Module 3: Implementing Simulations
  • 3.1: Executing Equations (Running Models)
  • 3.2: Model Specification and Parameterization
  • 3.3: Common Simulation Methodologies (And Their Applications)
• Module 4: Data Analysis
  • 4.1: Data Visualization
  • 4.2: Statistical Analysis Methods (?)
  • 4.3: Model Fitting & Tuning: Examples
  • 4.4: Preparing Data for Publication & Sharing
• Module 5: Validity, Reliability, and Model Improvement
  • 5.1: Validation vs Verification
  • 5.2: Methods for Verifying a Model/Simulation
  • 5.3: Methods for Validating a Model/Simulation
  • 5.4: Pairing Models with Experiment
  • 5.5 Sharing Models
• Module 6: Suggested Best Practices
• Module 7: Key Biological Concepts
• Module 8: Worked Examples
• Model Paper: Ethanol and Acetaldehyde Metabolism in Human Beings
  • Introduction
  • Methods
  • Results
  • Model Expansion
  • Discussion
  • References
• Project: Reaction and Diffusion in an Antibody Detection Device
  • Introduction to antibody detection to establish viral exposure
  • Your antibody detector assignment
  • System specifications
  • Simulating diffusion of patient antibodies through the device
  • Task 1
  • Task 2
  • Task 3
  • Simulating diffusion and binding of patient antibodies in the device
  • Task 4
  • Task 5
  • Task 6
  • Task 7
• Project: MAXTox Manufacturing
  • Introduction
  • MAKTox Solution Attempt: Antitoxin
  • Engineering Viable Solutions
• Project: Circadian Rhythms
  • Introduction
  • Feedback Loops and Oscillators
  • Model Development
  • Phosphorylation of PER and CRY
  • Jet Lag Simulation
  • Interpretation Questions
  • Integration and Expansion Questions
  • Atypical Circadian Rhythms
• Project: Chemotaxis Adaptation
  • Introduction to Papers
  • Task 1: The Basics of the Chemotaxis Network
  • Task 2: The Spiro Model
  • Task 3: The Barkai Model
  • Task 4: Robustness and Perfect Adaptation
  • Task 5: Coding the Chemotaxis Model
  • Task 6: Modeling Perfect Adaptation
  • Conclusions
  • References
• Signaling pathway dynamics
  • Section 0: Three-component networks and loops
  • Section 1: Coherent Feed Forward Loop
  • Section 2: Incoherent Feed Forward Loop
  • Section 3: Using data and logic to identify network structures
• Chemical Reactor Stability and Sensitivity
  • Introduction
  • Task 1
  • Energy balance in the isothermal case
  • Task 2
  • Steady-state mass and energy balance equations for reactor
  • Task 3
  • Exothermic reactions and Multiple Steady States
  • Extinction/Ignition and Van Heerden
• Morphogen Gradients
  • Introduction
  • Model
  • Results
• Equations of State
  • What is fugacity?
  • Gibbs Free Energy and Ideal Gas Law
  • Van Der Waals Equation of State
  • Peng-Robinson Equation of State
  • Example 1
  • Example 2
  • Citations
• Appendix #: Catalog of Jupyter Notebooks
  • Instructional Modules
  • Projects
  • Example Papers

Indices and tables

• Index

• Module Index

• Search Page